import tempfile
import unittest
from pathlib import Path
from shutil import copyfile

from transformers import BatchEncoding, MarianTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, slow
from transformers.utils import is_sentencepiece_available, is_tf_available, is_torch_available


if is_sentencepiece_available():
     from transformers.models.marian.tokenization_marian import VOCAB_FILES_NAMES, save_json

from ...test_tokenization_common import TokenizerTesterMixin


_SCREAMING_SNAKE_CASE 		=      get_tests_dir("""fixtures/test_sentencepiece.model""")

_SCREAMING_SNAKE_CASE 		=      {"""target_lang""": """fi""", """source_lang""": """en"""}
_SCREAMING_SNAKE_CASE 		=      """>>zh<<"""
_SCREAMING_SNAKE_CASE 		=      """Helsinki-NLP/"""

if is_torch_available():
     _SCREAMING_SNAKE_CASE 		=      """pt"""
elif is_tf_available():
     _SCREAMING_SNAKE_CASE 		=      """tf"""
else:
     _SCREAMING_SNAKE_CASE 		=      """jax"""
@require_sentencepiece
class SCREAMING_SNAKE_CASE_		(      __lowerCAmelCase  ,     unittest.TestCase		):
   __lowerCAmelCase           =				MarianTokenizer
   __lowerCAmelCase           =				False
   __lowerCAmelCase           =				True







   def 						lowerCamelCase_	(     self						:						Optional[int]				):





    """simple docstring"""


    super().setUp()
    UpperCamelCase			  =      ["""</s>""", """<unk>""", """▁This""", """▁is""", """▁a""", """▁t""", """est""", """\u0120""", """<pad>"""]
    UpperCamelCase			  =      dict(zip(lowerCamelCase_   ,   range(len(lowerCamelCase_				)				)				)				)
    UpperCamelCase			  =      Path(self.tmpdirname				)
    save_json(lowerCamelCase_   ,   save_dir / VOCAB_FILES_NAMES["""vocab"""]				)
    save_json(lowerCamelCase_   ,   save_dir / VOCAB_FILES_NAMES["""tokenizer_config_file"""]				)
    if not (save_dir / VOCAB_FILES_NAMES["source_spm"]).exists():
     copyfile(lowerCamelCase_   ,   save_dir / VOCAB_FILES_NAMES["""source_spm"""]				)
     copyfile(lowerCamelCase_   ,   save_dir / VOCAB_FILES_NAMES["""target_spm"""]				)

    UpperCamelCase			  =      MarianTokenizer.from_pretrained(self.tmpdirname				)
    tokenizer.save_pretrained(self.tmpdirname				)







   def 						lowerCamelCase_	(     self						:						Optional[Any]   ,   **lowerCamelCase_						:						Tuple				):





    """simple docstring"""


    return MarianTokenizer.from_pretrained(self.tmpdirname   ,   **lowerCamelCase_				)







   def 						lowerCamelCase_	(     self						:						Union[str, Any]   ,   lowerCamelCase_						:						Dict				):





    """simple docstring"""


    return (
        "This is a test",
        "This is a test",
    )







   def 						lowerCamelCase_	(     self						:						Dict				):





    """simple docstring"""


    UpperCamelCase			  =      """</s>"""
    UpperCamelCase			  =      0

    self.assertEqual(self.get_tokenizer()._convert_token_to_id(lowerCamelCase_				)   ,   lowerCamelCase_				)
    self.assertEqual(self.get_tokenizer()._convert_id_to_token(lowerCamelCase_				)   ,   lowerCamelCase_				)







   def 						lowerCamelCase_	(     self						:						str				):





    """simple docstring"""


    UpperCamelCase			  =      list(self.get_tokenizer().get_vocab().keys()				)

    self.assertEqual(vocab_keys[0]   ,   """</s>"""				)
    self.assertEqual(vocab_keys[1]   ,   """<unk>"""				)
    self.assertEqual(vocab_keys[-1]   ,   """<pad>"""				)
    self.assertEqual(len(lowerCamelCase_				)   ,   9				)







   def 						lowerCamelCase_	(     self						:						Optional[Any]				):





    """simple docstring"""


    self.assertEqual(self.get_tokenizer().vocab_size   ,   9				)







   def 						lowerCamelCase_	(     self						:						int				):





    """simple docstring"""


    UpperCamelCase			  =      MarianTokenizer.from_pretrained(f"""{ORG_NAME}opus-mt-en-de"""				)
    UpperCamelCase			  =      en_de_tokenizer(["""I am a small frog"""]   ,   return_tensors=lowerCamelCase_				)
    self.assertIsInstance(lowerCamelCase_   ,   lowerCamelCase_				)
    UpperCamelCase			  =      [38, 121, 14, 697, 3_8848, 0]
    self.assertListEqual(lowerCamelCase_   ,   batch.input_ids[0]				)

    UpperCamelCase			  =      tempfile.mkdtemp()
    en_de_tokenizer.save_pretrained(lowerCamelCase_				)
    UpperCamelCase			  =      [x.name for x in Path(lowerCamelCase_				).glob("""*"""				)]
    self.assertIn("""source.spm"""   ,   lowerCamelCase_				)
    MarianTokenizer.from_pretrained(lowerCamelCase_				)







   def 						lowerCamelCase_	(     self						:						Union[str, Any]				):





    """simple docstring"""


    UpperCamelCase			  =      self.get_tokenizer()

    UpperCamelCase			  =      tok(
        ["""I am a small frog""" * 1000, """I am a small frog"""]   ,   padding=lowerCamelCase_   ,   truncation=lowerCamelCase_   ,   return_tensors=lowerCamelCase_				)
    self.assertIsInstance(lowerCamelCase_   ,   lowerCamelCase_				)
    self.assertEqual(batch.input_ids.shape   ,   (2, 512)				)







   def 						lowerCamelCase_	(     self						:						Union[str, Any]				):





    """simple docstring"""


    UpperCamelCase			  =      self.get_tokenizer()
    UpperCamelCase			  =      tok(["""I am a tiny frog""", """I am a small frog"""]   ,   padding=lowerCamelCase_   ,   return_tensors=lowerCamelCase_				)
    self.assertIsInstance(lowerCamelCase_   ,   lowerCamelCase_				)
    self.assertEqual(batch_smaller.input_ids.shape   ,   (2, 10)				)







   @slow
   def 						lowerCamelCase_	(     self						:						List[Any]				):





    """simple docstring"""


    UpperCamelCase			  =      {"""input_ids""": [[4_3495, 462, 20, 4_2164, 1369, 52, 464, 132, 1703, 492, 13, 7491, 3_8999, 6, 8, 464, 132, 1703, 492, 13, 4669, 3_7867, 13, 7525, 27, 1593, 988, 13, 3_3972, 7029, 6, 20, 8251, 383, 2, 270, 5866, 3788, 2, 2353, 8251, 1_2338, 2, 1_3958, 387, 2, 3629, 6953, 188, 2900, 2, 1_3958, 8011, 1_1501, 23, 8460, 4073, 3_4009, 20, 435, 1_1439, 27, 8, 8460, 4073, 6004, 20, 9988, 375, 27, 33, 266, 1945, 1076, 1350, 3_7867, 3288, 5, 577, 1076, 4374, 8, 5082, 5, 2_6453, 257, 556, 403, 2, 242, 132, 383, 316, 492, 8, 1_0767, 6, 316, 304, 4239, 3, 0], [148, 1_5722, 19, 1839, 12, 1350, 13, 2_2327, 5082, 5418, 4_7567, 3_5938, 59, 318, 1_9552, 108, 2183, 54, 1_4976, 4835, 32, 547, 1114, 8, 315, 2417, 5, 92, 1_9088, 3, 0, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100], [36, 6395, 1_2570, 3_9147, 1_1597, 6, 266, 4, 4_5405, 7296, 3, 0, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100]], """attention_mask""": [[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]}  # noqa: E501
    # fmt: on

    self.tokenizer_integration_test_util(
        expected_encoding=lowerCamelCase_   ,   model_name="""Helsinki-NLP/opus-mt-en-de"""   ,   revision="""1a8c2263da11e68e50938f97e10cd57820bd504c"""   ,   decode_kwargs={"""use_source_tokenizer""": True}   ,   )







   def 						lowerCamelCase_	(     self						:						List[str]				):





    """simple docstring"""


    UpperCamelCase			  =      MarianTokenizer.from_pretrained("""hf-internal-testing/test-marian-two-vocabs"""				)

    UpperCamelCase			  =      """Tämä on testi"""
    UpperCamelCase			  =      """This is a test"""

    UpperCamelCase			  =      [76, 7, 2047, 2]
    UpperCamelCase			  =      [69, 12, 11, 940, 2]

    UpperCamelCase			  =      tokenizer(lowerCamelCase_				).input_ids
    self.assertListEqual(lowerCamelCase_   ,   lowerCamelCase_				)

    UpperCamelCase			  =      tokenizer(text_target=lowerCamelCase_				).input_ids
    self.assertListEqual(lowerCamelCase_   ,   lowerCamelCase_				)

    UpperCamelCase			  =      tokenizer.decode(lowerCamelCase_   ,   skip_special_tokens=lowerCamelCase_				)
    self.assertEqual(lowerCamelCase_   ,   lowerCamelCase_				)

def 			lowercase(	UpperCamelCase_							,					UpperCamelCase_							,					UpperCamelCase_       )		->	list:







 '''simple docstring'''
 UpperCamelCase			  =      len(UpperCamelCase_       )
 UpperCamelCase			  =      [[0] * n for i in range(UpperCamelCase_       )]
 for i in range(UpperCamelCase_       ):
  UpperCamelCase			  =      y_points[i]

 for i in range(2							,					UpperCamelCase_       ):
  for j in range(UpperCamelCase_							,					UpperCamelCase_       ):
   UpperCamelCase			  =      (
       (xa - x_points[j - i + 1]) * q[j][i - 1]
       - (xa - x_points[j]) * q[j - 1][i - 1]
   ) / (x_points[j] - x_points[j - i + 1])

 return [q[n - 1][n - 1], q]


if __name__ == "__main__":
     import doctest

     doctest.testmod()
